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Model-based multi-objective optimal control of a VRF (variable refrigerant flow) combined system with DOAS (dedicated outdoor air system) using genetic algorithm under heating conditions

机译:基于遗传算法在加热条件下基于模型的VRF(可变制冷剂流量)与DOAS(专用室外空气系统)组合系统的多目标最优控制

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摘要

A VRF (variable refrigerant flow) combined system adopting a DOAS (dedicated outdoor air system) has been proposed to reduce the total energy consumption while satisfying IAQ (indoor air quality) and THC (thermal and humidity comfort) with minimum outdoor air. The objective of this study is to develop,a model-based multi-objective optimal control strategy for the VRF combined system with multi-zone in order to optimize the multi-objective functions of the THC, IAQ, and total energy consumption. The performance of the VRF combined system was evaluated using the EnergyPlus model. The VRF combined system was optimized by GA (genetic algorithm) and RSM (response surface methodology) with the multi-objective functions of the THC, IAQ and total energy consumption. The proposed multi-objective optimal control strategies (A and B) were compared with the TS (time schedule) strategy and the DCVH (demand controlled ventilation with humidifying). Optimal control strategy B reduced the total energy consumption by 20.4% and increased the ratio of the hours satisfying the extended comfort zone by 19.1% compared to the DCVH strategy. (C) 2016 Elsevier Ltd. All rights reserved.
机译:已提出采用DOAS(专用室外空气系统)的VRF(可变制冷剂流量)组合系统,以减少总能耗,同时用最少的室外空气满足IAQ(室内空气质量)和THC(热和湿气舒适度)。本研究的目的是为多区域VRF组合系统开发一种基于模型的多目标最优控制策略,以优化THC,IAQ和总能耗的多目标功能。使用EnergyPlus模型评估了VRF组合系统的性能。 VGA组合系统通过GA(遗传算法)和RSM(响应面方法)进行了优化,并具有THC,IAQ和总能耗的多目标功能。将拟议的多目标最优控制策略(A和B)与TS(时间表)策略和DCVH(加湿需求控制通风)进行了比较。与DCVH策略相比,最佳控制策略B降低了20.4%的总能耗,并使满足扩展舒适区的小时数比例提高了19.1%。 (C)2016 Elsevier Ltd.保留所有权利。

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